Carbon allocation in forest ecosystem - case studies from young pine stands

Priwitzer, Tibor; Pajtík, Jozef; Konôpka, Bohdan; Ištoňa, J.; Pavlenda, Pavel

doi:10.2478/v10114-009-0007-2

Cited by 3 publications

(1 citation statement)

References 13 publications

(3 reference statements)

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“…General data description and predictor selection. The calculated SOC values in the depth 0-30 cm ranging from 0.07 to 38.59 kg/m 2 , with a mean of 10.30 kg/m 2 (Table 1) correspond to values compiled by Lal (2005) for temperate forests, as well as those reported for Germany and other Central European countries (Wiesmeier et al 2012), Slovakia (Priwitzer et al 2009), Austria (Baumgarten et al 2021), Spain (Calvo de Anta et al 2020), or EU (De Vos et al 2015). Prietzel and Christophel (2014) found slightly lower values in mineral topsoils in German Alps, which may be caused by higher elevations and consequently higher proportion of SOC in forest floor, and by the rock fragments that were not taken into account in our study.…”

Section: Resultssupporting

confidence: 76%

Predictors for digital mapping of forest soil organic carbon stocks in different types of landscape

Borůvka¹,

Vašát²,

Šrámek³

et al. 2022

Soil Water Res.

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Forest soils have a high potential to store carbon and thus mitigate climate change. The information on spatial distribution of soil organic carbon (SOC) stocks is thus very important. This study aims to analyse the importance of environmental predictors for forest SOC stock prediction at the regional and national scale in the Czech Republic. A big database of forest soil data for more than 7 000 sites was compiled from several surveys. SOC stocks were calculated from SOC content and bulk density for the topsoil mineral layer 0–30 cm. Spatial prediction models were developed separately for individual natural forest areas and for four subsets with different altitude range, using random forest method. The importance of environmental predictors in the models strongly differs between regions and altitudes. At lower altitudes, forest edaphic series and soil classes are strong predictors, while at higher altitudes the predictors related to topography become more important. The importance of soil classes depends on the pedodiversity level and on the difference in SOC stock between the classes. The contribution of forest types as predictors is limited when one (mostly coniferous) type dominates. Better prediction results can be obtained in smaller, but consistent regions, like some natural forest areas.

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Section: Resultssupporting

confidence: 76%

Predictors for digital mapping of forest soil organic carbon stocks in different types of landscape

Borůvka¹,

Vašát²,

Šrámek³

et al. 2022

Soil Water Res.

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Species Composition and Carbon Stock of Tree Cover at a Postdisturbance Area in Tatra National Park, Western Carpathians

Konôpka

Šebeň

Pajtík

2019

Mountain Research and Development

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Differential Influence of No-Tillage and Precipitation Pulses on Soil Heterotrophic and Autotrophic Respiration of Summer Maize in the North China Plain

Leng

et al. 2020

Agronomy

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It is important to strengthen the studies on the response of soil respiration components to tillage practices and natural precipitation in cropland. Therefore, soil heterotrophic respiration (RH) and autotrophic (RA) respiration were monitored by a root exclusion method in the North China Plain (NCP). The tillage practices included no-tillage (NT) and conventional tillage (CT), and the study periods were the summer maize growth stages in 2018 and 2019. RH, RA, soil water content and temperature were measured continuously for 113 days by an automatic sampling and analysis system. The soil RH values on bright days and rain-affected days were higher under NT in 2018 (14.22 and 15.06 g CO2 m−2 d−1, respectively) than in 2019 (8.25 and 13.30 g CO2 m−2 d−1, respectively). However, the RA values on bright days and rain-affected days were lower under NT in 2018 (4.74 and 4.97 g CO2 m−2 d−1, respectively) than in 2019 (5.67 and 6.93 g CO2 m−2 d−1, respectively). Moreover, NT decreased RH but increased RA compared to CT in 2019. Compared to bright days, the largest increase in both RH and RA after rain pulses was under CT in 2019 (6.75 and 1.80 g CO2 m−2 d−1, respectively). Soil water content and soil temperature were higher in 2018 than in 2019. Moreover, NT increased soil water content and decreased soil temperature on bright days compared to CT in 2019. Furthermore, soil temperature accounted for more variations in RH on bright days and rain-affected days, but soil water content had a greater influence on RA on bright days. However, after precipitation, higher soil water content decreased RA under NT in 2018, while soil water content was positively related to RA under CT in 2019. This study determined the differential response of RH and RA to tillage practices and natural precipitation pulses, and we confirmed that excessively dry soil increases soil carbon loss after rain events in the NCP.

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Carbon allocation in forest ecosystem - case studies from young pine stands

Cited by 3 publications

References 13 publications

Predictors for digital mapping of forest soil organic carbon stocks in different types of landscape

Predictors for digital mapping of forest soil organic carbon stocks in different types of landscape

Species Composition and Carbon Stock of Tree Cover at a Postdisturbance Area in Tatra National Park, Western Carpathians

Differential Influence of No-Tillage and Precipitation Pulses on Soil Heterotrophic and Autotrophic Respiration of Summer Maize in the North China Plain

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